Background: Prostate Cancer (PCa) is the most common malignant tumor in males and Biochemical Relapse (BCR) consists of a challenging scenario compared to primary staging due to small volume of disease and low PSA levels. Prostate-Specific Membrane Antigen (PSMA), Positron Emission Tomography (PET) presents superior performance and strongly affects therapeutic choice.

Objective: The objective of this study was to evaluate the impact of PSMA PET, compared to conventional imaging methods, on BCR therapeutic approach in patients treated at the public Brazilian health system.

Methods: 128 patients diagnosed with BCR were evaluated using PSMA after conventional imaging. Disease extension defined by PET was compared with conventional imaging; staging / extension changes and therapeutic management impact were then determined. PET comparison with conventional imaging and decision-making changes were analyzed using descriptive statistics and statistical tests.

Results: Disease detection rate was 60% and 41% using PSMA and conventional exams, respectively. PET detection rates and sensitivity increased proportionally to the increase in PSA levels and no statistically significant difference was observed in the rate of disease detection between patients with and without androgen blockade. After disclosure of PET findings and the results of the confrontation with conventional imaging, the board changed the management decision in 36% of the patients with and locoregional treatment indication was predominant.

Conclusions: The impact of PSMA on BCR therapeutic management, when compared to conventional exams, is significant, favoring the indication of locoregional salvage treatments and PSMA cost-effectiveness over traditional investigation has been demonstrated in other countries.

Background: Patients are presenting to emergency departments with nonspecific signs and symptoms that can be associated with lifethreatening conditions.

Methods: A 61-year-old patient presented with a left-sided neck mass that had rapidly increased in size. Ultrasonography revealed a 5x4 cm mass at levels IIa-III with reduced echogenicity and posterior enhancement. There were no B symptoms or other medical conditions. Computed Tomography (CT) showed a mass suspicious of malignant lymphoma.

Results: We resected the cystic structure and took tongue base biopsies. Histology revealed a neck cyst and poorly differentiated non-keratinizing squamous cell carcinoma in the cyst wall. Positron emission tomography with CT showed a mild elevation in glucose metabolism. There were no focal areas of residual malignancy or metastatic disease. No primary tumor was found.

Conclusion: Lesions with the morphology of a cystic mass can be malignant, especially in patients over 40 years. Cystic neck metastases are often p-16 positive. 

This paper presents four Key Performance Indicators (KPIs) designed as crucial metrics for assessing the effectiveness and influence of IHE [1] Cross-enterprise Document Sharing (XDS) based Health Information Exchange (HIE) infrastructures, with a focus on supporting collaborative healthcare and care coordination use-cases. The identified KPIs center around registered document volumes (70 million), exchanged DICOM studies (91.000/month), exchanged documents (525.000/month), and the count of registered patients (21 million). Through a comprehensive analysis of these KPIs, the study draws insights from an IHE XDS-based health information exchange in the Netherlands, encompassing data from 27 healthcare institutions utilizing the Dutch XDS Cloud service. The findings contribute valuable insights that extend beyond the specific context, providing applicable knowledge to the broader landscape of XDS-based health information exchanges. The KPIs identified in this paper show evidence that the Dutch XDS Cloud Service successfully supports care coordination and patient referrals use-cases in the Netherlands.

Brain Glioma is a common invasive brain tumor arising from glial cells, with various clinical presentations and risk factors like ionizing radiation and heterogeneity. Astrocytoma, named after astrocytes, is graded based on abnormality. Glioblastoma Multiforme (GBM) is the most malignant type, distinguished by histologic features and pathological diagnosis based on physical appearance, genetics, nuclear atypia, and cell mitotic activity. This paper explores variations in radiologic features and the correlation between GBM in CT and MRI modalities. The proposal of the GMB literature review was undertaken by searching the databases: Google Scholar, Cochrane Library, EBSCOHOST, Medline, Healthline Website, Medscape, PubMed, PsycINFO and CINAHL. 60 papers published till 2023 were reviewed. It was found that a GBM patient presents with various symptoms that vary with the tumor site. Moreover, GBM is characterized by rapid growth and invasion facilitated by cell migration and degradation of the extracellular matrix. Thus, despite technological advances in surgery and radio-chemotherapy, Glioblastoma remains largely incurable. Henceforth the great need for new approaches to study Glioblastoma and to design optimized therapies such as viral therapy [1]. However, to confirm the presence and the extent of tumor, various invasive and non-invasive imaging techniques require employment. Where an obvious variation between the normal brain anatomy and human brain damaged by the Glioblastoma is illustrated. Furthermore, understanding the molecular and genetic mechanisms underlying its aggressive behavior may lead to better management, appropriate therapies, and good outcomes [2].

Objective : The Thyroid Imaging Reporting and Data Systems (TI-RADS) is a standard terminology that classifies thyroid nodules according to their potential risk of cancer to reduce unnecessary biopsies, minimize variations in interpreting thyroid nodule images, and improve diagnostic accuracy. This study aims to comprehensively review articles that utilize AI techniques to develop decision support systems for analyzing ultrasound images of thyroid nodules, following different TIRADS guidelines.

Materials and Methods : In this review, we followed a five-step process. This included identifying the key research questions, outlining the literature search strategies, establishing criteria for including and excluding studies, assessing the quality of the studies, and extracting the relevant data. We created a comprehensive search string to gather all relevant English-language studies up to January 2024 from the PubMed, Scopus, and Web of Science databases, and we also followed the PRISMA diagram.

Results: In this review, forty-four papers were included, and the most important properties of these papers, including dataset characteristics, AI technical specifications, results and outcome metrics, metrics, limitations, and contributions, were extracted.

Conclusion: In this review, we evaluated the technical characteristics and various aspects used in the development of artificial intelligence CAD systems based on various TI-RADS. This review demonstrates that AI advancements, especially deep learning methods, have significantly enhanced CAD systems for evaluating thyroid nodules. However, comprehensive datasets, multimodal images, and standard evaluation metrics are needed to further enhance machine learning models. Our study aims to provide researchers and physicians with a summary of the current advancements in this field to guide future investigations.